SVM is not the only solution to these problems. For many search engine applications, it isn't even likely to be the best. Regularized logistic regression is a strong candidate as are random forests and boosted trees.
Beware of any author who claims that their algorithm for machine learning that claims to be better than all others. The algorithm may well have some virtues, but it is unlikely to be universal. It is more likely that the author who claims this simply has a limited view of the range of things that might need to be done. On 3/29/08 10:23 AM, "Marko Novakovic" <[EMAIL PROTECTED]> wrote: > The implementation of SVM algorithm at Hadoop platform > > Abstract: > > I have been researching in Search Engines > functionalities, like ranking, presenting relevant > page to users, etc. > I noted that the most usable solution for search > engines is Support Vector Machine. > The best solution for determination relevant page > ranking for user based search result is SVM. > Reference to this problem is article: > T. Joachims, F. Radlinski: "Search Engines that > Laerning from Implicit Feedback," IEEE Computer, > August 2007, pp 38 > According to SVM is very complex algorithm, which has > a lot of operations, > I decided to implement SVM algorithm at Hadoop > platform. > > Dear Apache, > > My Idea: > > I have idea to implement model and solution for > retrieving relevant ranking Web pages driven by user's > past behavior. > According to SE-s have a lot of crawled Web pages, > this operation must be realized distributed if we want > to obtain results in real time and have fresh learned > database. > So we should paralelize all algorithms, which are used > for processing Web pages. > So I decided to implement the most used and exploited > algorithm in machine learning, deployed in operating > Web pages. > I also, choose SVM algorithm because it is very > complex algorithm for implementation > and I like temptations and I am not affraid of hard > tasks. > I tend to achieve most a big degree of performances > through paralelization. > I will exploit working on this project for writing new > article about deployment of clustering at SE-a. > I have prepared to this project reading articles: > [1] C. Burges, "A Tutorial on Suppot Vector Machines > for Pattern Recognition," Kluwer Academin Publishers, > Boston > [2] R.E Fan, P.H Chen, C.J. Lin, "Working Set > Selection Using Second Order Information for Training > Support Vector Machines," Journal of Machine Learning > Research 6 (2005), pp 18891918 > I also have read Hadoop documentation and examined > your implementations of algoritm kMeans at this > platform. > > Methodoligies of Development: > > - Test Driven Development > - Deployment ANT an JUnit > - SDK: Eclipse > - SVN System for Versioning > - Javadoc > > About Me: > > My resume you can see at link > http://atisha34.googlepages.com/. > I also participate in some academic projects at my > college: > - Working at topic based Search Engine, called Grain, > which is in construction at my faculty. > - Tutorial about SE-s, mentored by professor Veljko > Milutinovic: "The New Avenues in Search Engines" > presentation: > http://atisha34.googlepages.com/Searchengines.ppt > abstract: > http://atisha34.googlepages.com/TheNewAvenuesinWebSearch.docx > I should publish article driven by this presentation > at IPSI Magazine. > - Other projects in which I participate aren't related > to machine learning and search engines. > > My Interests: > - Search Engines > - Software Engineering and Test Driven Development > - Machine Learning > - Database Modeling and OO Design > - ERP and Business Processes > > Sincerely Yours, > Marko Novakovic > > --- Karl Wettin <[EMAIL PROTECTED]> wrote: > >> Marko Novakovic skrev: >> >> Hi Marko, >> >>> I apply for SVM algorithm at Hadoop platform. >>> I hope that I will be accepted by Google and >> Appache, >>> I am serious in intention to do this jos as great. >> >> great news! Feel free to post your proposal here >> too. >> >> >> karl >> > > > > > ______________________________________________________________________________ > ______ > Looking for last minute shopping deals? > Find them fast with Yahoo! Search. > http://tools.search.yahoo.com/newsearch/category.php?category=shopping >
